Opposition Skill Efficiency During Professional Rugby Union Official Games Is Related to Horizontal Force-Production Capacities in Sprinting

Effects of Repeated High-Intensity Effort Training or Repeated Sprint Training on Repeated High-Intensity Effort Ability and In-Game Performance in Professional Rugby Union Players

ABSTRACT

Glaise, P, Rogowski, I, and Martin, C. Effects of repeated high-intensity effort training or repeated sprint training on repeated high-intensity effort ability and in-game performance in professional rugby union players. J Strength Cond Res 38(5): 932-940, 2024-This study investigated the effects of repeated high-intensity efforts (RHIE) training compared with repeated sprint exercise (RSE) training on RHIE ability (RHIEa) and in-game performance in professional rugby union players. Thirty-nine, male, professional, rugby union players were randomly assigned to 3 training groups (RHIE training, RSE training, and control). Repeated high-intensity effort ability and high-intensity effort characteristics (including sprints, acceleration, and contact efforts) during official games were measured before and after a 10-week specific (RHIE, RSE, or control) training period. The results of this study showed that concerning RHIEa, both the RHIE and RSE training significantly increased the players' average sprint velocity ( p < 0.001, d = -0.39 and p < 0.001, d = -0.53 respectively), average sled push velocity (ASPV; p < 0.001, d = -0.81 and p = 0.017, d = -0.48 respectively), and RHIE score ( p < 0.001, d = -0.72 and p < 0.001, d = -0.60 respectively). Repeated high-intensity effort training trended in a smaller increase in average sprint velocity than RSE training, a larger increase in ASPV, and a similar increase in RHIE score. Concerning in-game high-intensity efforts, both the RHIE and RSE training produced significant improvements in the number of sprints ( p = 0.047, d = -0.28 and p < 0.001, d = -0.47 respectively), total distance ( p < 0.001, d = -0.50 and p = 0.002, d = -0.38 respectively), the number of accelerations ( p < 0.001, d = -0.37 and p = 0.003, d = -0.32 respectively), and contact rate ( p < 0.001, d = -0.97 and p = 0.020, d = -0.28 respectively). Conversely, the magnitude of the increase in contact rate was almost twice as high in RHIE compared with RSE training. To conclude, the findings of this study were that both RSE and RHIE training are effective methods for developing RHIEa and in-game high-intensity efforts in professional rugby union. In practical applications, as the gains in certain abilities and game performance data differed depending on the training method chosen, we suggest that coaches choose the most appropriate method according to the profile of the players, their position, and the style of play they want to develop.

Individual In-Situ GPS-Derived Acceleration-Speed Profiling: Toward Automatization and Refinement in Male Professional Rugby Union Players

BACKGROUND

Recently a proof-of-concept was proposed to derive the soccer players' individual in-situ acceleration-speed (AS) profile from global positioning system (GPS) data collected over several sessions and games. The present study aimed to propose an automatized method of individual GPS-derived in-situ AS profiling in a professional rugby union setting.

METHOD

AS profiles of forty-nine male professional rugby union players representing 61.5 million positions, from which acceleration was derived from speed during 51 training sessions and 11 official games, were analyzed. A density-based clustering algorithm was applied to identify outlier points. Multiple AS linear relationships were modeled for each player and session, generating numerous theoretical maximal acceleration (A0), theoretical maximal running speed (S0) and AS slope (ASslope, i.e., overall orientation of the AS profile). Each average provides information on the most relevant value while the standard deviation denotes the method accuracy. In order to assess the reliability of the AS profile within the data collection period, data were compared over two 2-week phases by the inter-class correlation coefficient. A0 and S0 between positions and type of sessions (trainings and games) were compared using ANOVA and post hoc tests when the significant threshold had been reached.

RESULTS

All AS individual profiles show linear trends with high coefficient of determination (r2 > 0.81). Good reliability (Inter-class Correlation Coefficient ranging from 0.92 to 0.72) was observed between AS profiles, when determined 2 weeks apart for each player. AS profiles depend on players' positions, types of training and games. Training and games data highlight that highest A0 are obtained during games, while greatest S0 are attained during speed sessions.

CONCLUSIONS

This study provides individual in-situ GPS-derived AS profiles with automatization capability. The method calculates an error of measurement for A0 and S0, of paramount importance in order to improve their daily use. The AS profile differences between training, games and playing positions open several perspectives for performance testing, training monitoring, injury prevention and return-to-sport sequences in professional rugby union, with possible transferability to other sprint-based sports.

KEY POINTS

AS profiles computed from rugby union GPS data provide positional benchmarks during training and competition. This study provides automatic detection of atypical data and the computation of error measurement of theoretical maximal acceleration and speed components. This refinement constitutes a step forward for a daily use of ecological data by considering data collection and method reliabilities. This easy-to-implement approach may facilitate its use to the performance management process (talent identification, training monitoring and individualization, return-to-sport).